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Source code for WWW'26 paper: "Byte-token Enhanced Language Models for Temporal Point Processes Analysis"

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Language-TPP

Source code for paper "Language-TPP: Integrating Temporal Point Processes with Language Models for Event Analysis"

Overview

Please refer to the following script for a demo of the proposed model:

  • Language_TPP_0___5B/modeling_langtpp.py: revised version of the original Qwen2 model with the computation of log-likelihood values of TPPs. Note that pretrained model weights are not included in this repository and we plan to release them soon.
  • demo.py: demo script for the revised Qwen2 model, along with the proposed byte tokens and inference process.

Quick Start

Use uv to set up the environment:

# On macOS and Linux.
curl -LsSf https://astral.sh/uv/install.sh | sh

uv sync

TODO

  • Release pretrained model weights
  • Release training scripts and documentation
  • Release evaluation scripts and benchmarks

Acknowledgments

This codebase builds upon the architecture and implementation of Qwen2.

Citation

If you find this work useful in your research, please consider citing our paper:

@article{kong2024languagetpp,
  title={Language-TPP: Integrating Temporal Point Processes with Language Models for Event Analysis},
  author={Kong, Quyu and Zhang, Yixuan and Liu, Yang and Tong, Panrong and Liu, Enqi and Zhou, Feng},
  journal={arXiv preprint},
  year={2024}
}

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Source code for WWW'26 paper: "Byte-token Enhanced Language Models for Temporal Point Processes Analysis"

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